A compact, fast embedding specialist tuned specifically for question-answering retrieval tasks. It excels at matching questions to relevant passages using dot-product similarity, making it snappy and practical for search pipelines. Its small size (6 layers) means it trades some nuance for speed — great for high-throughput scenarios, less suited for capturing subtle semantic distinctions.